In electricity distribution systems, loss occurs when current flows through the conductors in the system. The energy loss through a conductor can be calculated according to I2R, where I is the current through a conductor whose resistance is R. The net demand and current flows on a distribution circuit depend on the loading and the voltage profile on the feeders. Net demand is the net energy delivered from the substations into the distribution circuits and is the summation of the total energy loss on all the conductors in the circuits and the total energy delivered at all load connection points. Reactive compensation can reduce unnecessary current flows attributable to reactive power flows and in turn reduce losses. Voltage regulation affects the effective loading of feeders, as well as the energy losses.
Voltage and Var optimization (VVO) systems are employed in electricity distribution systems to optimize the distribution of voltages and currents on distribution systems. VVO systems endeavor to maximize efficiency of energy delivery by controlling voltage regulators (Voltage) and reactive power resources (Var) by employing online system models and demand forecasts.
With reference to FIG. 1, an electricity distribution network is shown. As can be seen, a substation provides power to a plurality of loads via a distribution system. Distributed at various points in the distribution network are capacitor banks C that may be fixed or switched. The connectivity of the network and the status of the various pieces of equipment, such as transformers, loads, capacitors, voltage regulators, are monitored. Monitored data may include voltage, current and/or power at or through various points or conductors. This information is transmitted to a distribution management system (DMS) or a substation automation system. Upon receiving the updated status information, the system model within the DMS is updated. A load forecast is performed based on the SCADA data, customer billing data, and/or data collected from advanced metering infrastructure (AMI).
The VVO, utilizing the load forecasts, the system model, and the available control information, then determines the best tap settings for the voltage regulators and on load tap change (OLTC) transformers located either at the substation or on the feeders, and the Var resources such as switched shunt capacitors or reactors. Control commands are then transmitted back to the various elements in the distribution grid where the control actions are carried out, bring the system to a more efficient operating state. Voltage regulation optimization (VRO) and var optimization (VARO) are fundamental subsystems of a VVO system. The control variables for the VARO are the switchable or dispatchable reactive power sources. The control variables for the VRO are the controllable taps of voltage regulating transformers.
The concept of optimizing energy delivery efficiency on electric distribution systems dates back several decades and many in the industry and the research communities have attempted to develop effective solution methodologies and processes. Most solution approaches proposed to date are applicable to small, very simplified academic models, and are not suitable for large scale, meshed, multi-source, multi-phase unbalanced distribution systems. The limitations in the methods are due to (1) the model being too simplified (i.e. radial, balanced network, balanced load, single source) to represent a real system, (2) the computation efficiency being so low that the solution can not be scaled for either online or offline applications for large system, or (3) the optimization power is very limited.
Thus, there is a need in the art for an optimization solution that is applicable to large scale, meshed, multi-source, multi-phase unbalanced distribution systems, and that is efficient for online applications.